# quantum_audit_system.py
import hashlib
import numpy as np

class QuantumAuditSystem:
    """
    Simulates quantum-resistant verification using zk-STARKs
    and quantum random walk tags (classical simulation)
    """
    
    def __init__(self):
        self.entropy_factor = 1.2  # Initial entropy expansion coefficient
    
    def generate_quantum_tag(self, client_id, timestamp):
        """
        Simulate quantum random walk tag generation
        
        Args:
            client_id (int): Unique client identifier
            timestamp (int): Training round
            
        Returns:
            bytes: Simulated quantum tag (hash)
        """
        # In real implementation: Quantum random walk evolution
        base = f"{client_id}-{timestamp}-{self.entropy_factor}".encode()
        return hashlib.sha3_256(base).digest()
    
    def verify_consistency(self, tags):
        """
        Verify consistency of quantum tags across clients
        
        Args:
            tags (list): List of tags from all clients
            
        Returns:
            bool: True if all tags match, False otherwise
        """
        return all(tag == tags[0] for tag in tags)
    
    def update_entropy(self, round_num, total_rounds):
        """
        Dynamically increase entropy over training rounds
        
        Args:
            round_num (int): Current training round
            total_rounds (int): Total number of training rounds
        """
        self.entropy_factor = 1.2 + 0.1 * np.tanh(round_num / total_rounds)
